Digital Data Collection In A Large Community-Based Injury Survey: Experience From A Low-Income Country Setting

Digital data collection is a secured, fast and flexible system by which almost every type of data can be collected. Through this system, data can be collected anywhere in the world. It provides an opportunity to modify the survey questionnaire at any time during the survey. Data can be exported to Microsoft Excel, STATA, R, or SPSS for analysis. This study was designed to investigate the feasibility of digital data collection in a large-scale community survey in a low-income country. A large-scale community-based injury survey was designed to explore the drowning situation in southern part of Bangladesh. Twenty-one sub-districts, approximately 90 000 households and nearly 4, 05 000 populations were included in this survey. Paper form questionnaire was converted to digital form using REDCap (Research Electronic Data Capture) software and linked to android device through REDCap Mobile Apps. Fifty data collectors, 12 supervisors and 4 area coordinators were involved in the data collection process. An exploratory study was conducted to assess the feasibility, survey cost, time management of the digital data collection process. Face to face interview was conducted by data collectors, supervisors, data manager and research investigators of the survey. Ninety-eight percent respondents mentioned that, digital data collection was convenient compared to paper-based data collection. Among them 96% said, it required less time of data collection. It was also found that digital data collection required 25% less cost considering the questionnaire printing and data entry. This system provided an opportunity to monitor data quality on a regular basis and eliminate the error of data entry. Digital data collection is feasible and convenient, it required less time and resources. So, the benefit of digital data collection needs to disseminate more in low- and middle-income countries where resources are low.